Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Evaluation of Fertility Restorer Genotypes Using Multivariate Statistical Methods

Document Type : Original Article

Authors
F. Sohrabi 1
N. Babaeiyan Jelodar 2
N. Bagheri 3
1 M.Sc. Student, Department of Plant Biotechnology and Breeding, Faculty of Agricultural Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
2 Professor, Department of Plant Biotechnology and Breeding, Faculty of Agricultural Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
3 Assistant Professor, Department of Plant Biotechnology and Breeding, Faculty of Agricultural Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
10.47176/TDASS.2023.213
Abstract
In this study, eight rice fertility restorer genotypes were systematically evaluated based on a set of key morphological and agronomic characteristics. The primary aim was to identify superior restorer lines that could be effectively utilized in hybrid rice breeding programs. Multivariate statistical techniques, including principal component analysis (PCA) and cluster analysis, were applied to analyze the variation among genotypes and to elucidate the relationships among traits. The results of cluster analysis using Ward’s method categorized the genotypes into three distinct groups, with the IRI 347 line, which demonstrated the highest grain yield, forming a separate cluster, highlighting its potential as an elite restorer. PCA revealed that three independent principal components collectively explained 88.75% of the total phenotypic variation. The first principal component was primarily associated with yield-related traits such as filled grains per panicle and grain weight, indicating its central role in overall productivity. The second component was strongly linked to the number of sterile spikelets, reflecting reproductive efficiency, while the third component predominantly represented plant height. These findings provide valuable insights into the genetic diversity and trait interrelationships among rice restorer lines, facilitating the selection of high-performing genotypes for hybrid seed production and contributing to the development of more productive and resilient rice cultivars.
Keywords
Rice
Fertility Restorer Genes
Cluster Analysis
Morphological Traits
  • Bohra, A., Jha, U. C., Adhimoolam, P., Bisht, D., & Singh, N. P. (2016). Cytoplasmic male sterility (CMS) in hybrid breeding in field crops. Plant Cell Reports, 35(5), 967–993. https://doi.org/10.1007/s00299-015-1917-3
  • Kim, Y. J., & Zhang, D. (2018). Molecular control of male fertility for crop hybrid breeding. Trends in Plant Science, 23(1), 53–65. https://doi.org/10.1016/j.tplants.2017.10.001
  • Singh, S., Dey, S. S., Bhatia, R., Kumar, R., & Behera, T. K. (2019). Current understanding of male sterility systems in vegetable Brassicas and their exploitation in hybrid breeding. 3 Biotech, 9(9), 324. https://doi.org/10.1007/s13205-019-1847-5
  • Mohammadi, S. A., & Prasanna, B. M. (2003). Analysis of genetic diversity in crop plants—Salient statistical tools and considerations. Crop Science, 43(4), 1235–1248. https://doi.org/10.2135/cropsci2003.1235
  • Crossa, J., & Franco, J. (2004). Statistical methods for classifying genotypes. Euphytica, 137(1), 19–37. https://doi.org/10.1023/B:EUPH.0000040500.86428.e8
  • Franco, J., Crossa, J., Taba, S., & Shands, H. (2005). A sampling strategy for conserving genetic diversity in ex situ genebanks. Theoretical and Applied Genetics, 110(6), 1125–1138. https://doi.org/10.1007/s00122-005-1939-7
  • Kohnaki, M. E., Kiani, G., & Nematzadeh, G. (2013). Relationship between morphological traits in rice restorer lines at F3 generation using multivariate analysis. International Journal of Farming and Allied Sciences, 2(23), 572–577.
  • Ahmad, H. B., Habib, S., Chattha, W. S., Qamar, R., & Ali, Q. (2022). Evaluation of genetic diversity in maintainer and restorer inbreds of Helianthus annuus L. using multivariate techniques. Pakistan Journal of Agricultural Sciences, 59(1), 1–10. https://doi.org/10.21162/PAKJAS/22.1126
  • Hilli, H. J., Badiger, H., Biradar, A., Biradar, B. D., Nandihalli, B. S., Chittapur, B. M., & Lingaraju, N. (2021). Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.). Theoretical and Applied Genetics, 134(9), 2723–2735. https://doi.org/10.1007/s00122-021-03867-2
  • Saroj, S. K., Singh, M. N., Bhanu, A. N., Pathak, N., & Dhurai, S. Y. (2021). Genetics of fertility restoration and agronomic performance of CMS-based hybrids in pigeonpea. International Journal of Plant & Soil Science, 33(16), 220–231. https://doi.org/10.9734/ijpss/2021/v33i1630532
  • Sreewongchai, T., Pavadai, P., Sripongpang, S., Peyachoknagul, S., & Toojinda, T. (2010). Multivariate analysis of genetic diversity among some rice genotypes using morpho-agronomic traits. Kasetsart Journal (Natural Science), 44(5), 862–870.
  • International Rice Research Institute (IRRI). (1996). Standard evaluation system for rice. Manila, Philippines: IRRI.
  • Kiani, G., & Nemat-Zadeh, Gh. (2012). Genetic diversity of fertility-restoring lines in rice based on morphological traits (pp. 122–130).
  • Dorosti, H. (2000). Determination of genetic diversity based on agronomic traits of promising rice lines (Master's thesis, Faculty of Agriculture, Islamic Azad University, Karaj Branch).
  • Zinali Nejad, Kh., Mirlouhi, A., Nemat-Zadeh, Gh., & Rezaei, M. (2003). Genetic diversity of part of Iranian rice germplasm based on morphological traits. Journal of Agricultural Science and Natural Resources, 7(4), 199–213.
  • Rahim Soroush, H., Mesbah, M., Hosseinzadeh, H., & Bozorgi Pour, R. (2004). Genetic and phenotypic diversity and cluster analysis of quantitative and qualitative traits in rice. Nahal & Seed, 20, 167–182.
Transactions on Data Analysis in Social Science
Volume 5, Issue 4
Autumn 2023
Pages 213-218

  • Receive Date 16 August 2023
  • Revise Date 21 November 2023
  • Accept Date 19 December 2023